A method of tissue diagnosis based on mass spectrometry (MS) will be evaluated to distinguish the presence, type and grade of kidney, bladder and testicular cancers. The solvent-based method of desorption electrospray ionization (DESI) MS will be used to examine tissue directly and the resulting distribution of lipid-derived ions will be used to characterize the disease state of the tissue. This will be facilitated by building a data base of representative patterns of lipid ion intensities associated with tissue of different disease states and grades. Independent tissue characterization will be made by the standard methods of histopathology. Multivariate statistical tools will be used to evaluate the DESI-MS imaging data and software tools will be developed to correlate DESI molecular images with H&E stained optical images. (This aspect of the work will be led by Prof. Olga Vitek, a statistician and specialist in bioinformatics.) Special attention will be given to DESI solvents tht are morphologically non-destructive, so allowing DESI imaging to be inserted at any point in the surgical work-flow. The hypothesis underlying this effort is that the molecular information provided on lipid distributions in tissue is diagnostic of malignancy and complements the evaluation of tumor margins using histopathology. To test the capabilities of DESI-MS as a diagnostic tool for surgical applications, we will locate a DESI- equipped mass spectrometer in an Indiana University School of Medicine pathology laboratory. There, tests of the DESI method will be made in collaboration with a pathologist (Dr. Liang Cheng) using samples provided by a surgeon (Dr. Timothy Masterson). The experiments will occur in three stages: a) Off-line analysis of excised tissue without interfering with standard procedures used in surgical intervention. Tissue will be sprayed with a solvent and the mass spectra will be evaluated to reach a diagnosis (cancer, and its grade; or normal). These results will be compared with diagnoses obtained by standard histopathology. b) On-line tissue section imaging in parallel with standard pathology examination will be used to validate the capability of DESI-MS to yield pathological information on the time-scale of the surgery. These experiments will be used to validate/invalidate DESI-MS imaging as the primary step in clinical tissue- analysis workflow for tumor margin assessment. c) Rapid on-line DESI analysis of excised tissue during surgery will be used to check that the surface of resected tissue is clean of tumor margins. By using an indexing system the position of any incompletely removed cancerous tissue will be localized on a time scale suitable for surgical remediation. In preparation for future developments in which MS is utilized in the surgical suite, the performance of a small mass spectrometer will be improved to allow lipid analysis to mass 1000 Da at unit resolution.